Data Flow Graph
A Data Flow Graph (DFG) is a directed graph representation used in computing to model the flow of data between operations or processes, where nodes represent computations and edges represent data dependencies. It is a fundamental concept in compiler design, parallel computing, and data processing systems, enabling analysis and optimization of data movement and computation. DFGs help visualize and reason about how data is transformed and propagated through a system, making them essential for performance tuning and correctness verification.
Developers should learn about Data Flow Graphs when working on compiler optimization, parallel algorithm design, or data-intensive applications like machine learning pipelines, as they provide a clear model for identifying bottlenecks and dependencies. In fields such as high-performance computing or big data processing, understanding DFGs is crucial for optimizing resource usage and ensuring efficient execution by minimizing data movement and maximizing parallelism. It is also valuable in debugging and testing complex systems by tracing data transformations and dependencies.